In this Program Project we plan to expand the evidence indicating that life span is strongly inherited in families with exceptional longevity. Evidence from invertebrates implicates the evolutionarily conserved insulin/ insulin-like growth factor (IGF) signaling pathway in longevity, while evidence from the mouse models suggests the Growth Hormone (GH)/IGF pathway as most relevant to longevity. We hypothesize that genetic variation at loci involved in the GH/IGF signaling pathway can be related to individual differences in life span and the rate of aging in human populations. To address this hypothesis, we propose an approach to discover genetic alterations in the GH/IGF pathways that are enriched in families with exceptional longevity. This proposal is built on the strength of on going collaboration of Dr. Nir Barzilai (PI) with Drs. Yousin Sun (Molecular Human Geneticist from UTHSC) and Pinchas Cohen (IGF and binding protein biologist at UCLA), taking full advantage of the collection of phenotypes and DNA from the Jewish families with exceptional longevity and the appropriate controls and of several new technologies. A unique feature of this proposal is the combined use of genetic technology (exonic genotyping), the extensive biochemical (including IGF-1 and related protein analytes) and clinical phenotypes (including maximal height and age-related disease), which have been well-characterized and archived. This will allow us to establish a comprehensive genetic knowledge base, and associate the genetic information with the biochemical and clinical parallels. We will use advanced, comprehensive gene screen technology to discover all possible genetic variations in selected genes and their promoters in our probands with exceptional longevity and controls for association analysis (Suh), establish the allele frequency of these polymorphisms in all our study population for validation (Barzilai with the Genetic Core), and asses functional correlates of gene variants identified in association analysis using cellular assay systems (Cohen). The phenotypes for association analysis will include the serum levels of IGFs, and IGFBPs (Cohen) and the prevalence of several age-related diseases (Barzilai). The data and information will be made available through the Statistics and Data Management Core and its Bioinformatics Sharing facility. Newly discovered genes in this project will be made available for testing hypotheses in this longitudinal study (Projects 3 & 4).